Showing papers in "Brain Topography in 2010"

Towards a Cure for BCI Illiteracy

Abstract: Brain–Computer Interfaces (BCIs) allow a user to control a computer application by brain activity as acquired, e.g., by EEG. One of the biggest challenges in BCI research is to understand and solve the problem of “BCI Illiteracy”, which is that BCI control does not work for a non-negligible portion of users (estimated 15 to 30%). Here, we investigate the illiteracy problem in BCI systems which are based on the modulation of sensorimotor rhythms. In this paper, a sophisticated adaptation scheme is presented which guides the user from an initial subject-independent classifier that operates on simple features to a subject-optimized state-of-the-art classifier within one session while the user interacts the whole time with the same feedback application. While initial runs use supervised adaptation methods for robust co-adaptive learning of user and machine, final runs use unsupervised adaptation and therefore provide an unbiased measure of BCI performance. Using this approach, which does not involve any offline calibration measurement, good performance was obtained by good BCI participants (also one novice) after 3–6 min of adaptation. More importantly, the use of machine learning techniques allowed users who were unable to achieve successful feedback before to gain significant control over the BCI system. In particular, one participant had no peak of the sensory motor idle rhythm in the beginning of the experiment, but could develop such peak during the course of the session (and use voluntary modulation of its amplitude to control the feedback application).

Methodology for Combined TMS and EEG

Abstract: The combination of transcranial magnetic stimulation (TMS) with simultaneous electroencephalography (EEG) provides us the possibility to non-invasively probe the brain’s excitability, time-resolved connectivity and instantaneous state. Early attempts to combine TMS and EEG suffered from the huge electromagnetic artifacts seen in EEG as a result of the electric field induced by the stimulus pulses. To deal with this problem, TMS-compatible EEG systems have been developed. However, even with amplifiers that are either immune to or recover quickly from the pulse, great challenges remain. Artifacts may arise from the movement of electrodes, from muscles activated by the pulse, from eye movements, from electrode polarization, or from brain responses evoked by the coil click. With careful precautions, many of these problems can be avoided. The remaining artifacts can be usually reduced by filtering, but control experiments are often needed to make sure that the measured signals actually originate in the brain. Several studies have shown the power of TMS–EEG by giving us valuable information about the excitability or connectivity of the brain.

A Review of Combined TMS-EEG Studies to Characterize Lasting Effects of Repetitive TMS and Assess Their Usefulness in Cognitive and Clinical Neuroscience

Abstract: Transcranial magnetic stimulation (TMS) has developed into a powerful tool for studying human brain physiology and brain–behavior relations. When applied in sessions of repeated stimulation, TMS can lead to changes in neuronal activity/excitability that outlast the stimulation itself. Such aftereffects are at the heart of the offline TMS protocols in cognitive neuroscience and neurotherapeutics. However, whether these aftereffects are of applied interest critically depends on their magnitude and duration, which should fall within an experimentally or clinically useful range without increasing risks and adverse effects. In this short review, we survey combined TMS-EEG studies to characterize the TMS-aftereffects as revealed by EEG to contribute to the characterization of the most effective and promising repetitive TMS-parameters. With one session of conventional repetitive TMS (of fixed pulse frequency), aftereffects were consistently comparable in magnitude to EEG-changes reported after learning or with fatigue, and were short-lived (<70 min). The few studies using recently developed protocols (such as theta burst stimulation) suggest comparable effect-size but longer effect-durations. Based on the reviewed data, it is expected that TMS-efficacy can be further promoted by repeating TMS-sessions, by using EEG-gated TMS to tailor TMS to current neuronal state, or by other, non-conventional TMS-protocols. Newly emerging developments in offline TMS research for cognitive neuroscience and neurotherapeutics are outlined.

Are females more responsive to emotional stimuli? A neurophysiological study across arousal and valence dimensions.

Abstract: Men and women seem to process emotions and react to them differently. Yet, few neurophysiological studies have systematically investigated gender differences in emotional processing. Here, we studied gender differences using Event Related Potentials (ERPs) and Skin Conductance Responses (SCR) recorded from participants who passively viewed emotional pictures selected from the International Affective Picture System (IAPS). The arousal and valence dimension of the stimuli were manipulated orthogonally. The peak amplitude and peak latency of ERP components and SCR were analyzed separately, and the scalp topographies of significant ERP differences were documented. Females responded with enhanced negative components (N100 and N200), in comparison to males, especially to the unpleasant visual stimuli, whereas both genders responded faster to high arousing or unpleasant stimuli. Scalp topographies revealed more pronounced gender differences on central and left hemisphere areas. Our results suggest a difference in the way emotional stimuli are processed by genders: unpleasant and high arousing stimuli evoke greater ERP amplitudes in women relatively to men. It also seems that unpleasant or high arousing stimuli are temporally prioritized during visual processing by both genders.

Sensitivity of MEG and EEG to Source Orientation

Abstract: An important difference between magnetoencephalography (MEG) and electroencephalography (EEG) is that MEG is insensitive to radially oriented sources. We quantified computationally the dependency of MEG and EEG on the source orientation using a forward model with realistic tissue boundaries. Similar to the simpler case of a spherical head model, in which MEG cannot see radial sources at all, for most cortical locations there was a source orientation to which MEG was insensitive. The median value for the ratio of the signal magnitude for the source orientation of the lowest and the highest sensitivity was 0.06 for MEG and 0.63 for EEG. The difference in the sensitivity to the source orientation is expected to contribute to systematic differences in the signal-to-noise ratio between MEG and EEG.

Combining TMS and EEG offers new prospects in cognitive neuroscience

Abstract: The combination of brain stimulation by transcranial magnetic stimulation (TMS) with simultaneous electroencephalographic (EEG) imaging has become feasible due to recent technical developments The TMS-EEG integration provides real-time information on cortical reactivity and connectivity through the analysis of TMS-evoked potentials (TEPs), and how functional activity links to behavior through the study of TMS-induced modulations thereof It reveals how these effects vary as a function of neuronal state, differing between individuals and patient groups but also changing rapidly over time during task performance This review discusses the wide range of possible TMS-EEG applications and what new information may be gained using this technique on the dynamics of brain functions, hierarchical organization, and cortical connectivity, as well as on TMS action per se An advance in the understanding of these issues is timely and promises to have a substantial impact on many areas of clinical and basic neuroscience

Mechanisms and applications of theta-burst rTMS on the human motor cortex.

Abstract: Theta-burst Stimulation (TBS) is a novel form of repetitive transcranial magnetic stimulation (rTMS). Applied over the primary motor cortex it has been successfully used to induce changes in cortical excitability. The advantage of this stimulation paradigm is that it is able to induce strong and long lasting effects using a lower stimulation intensity and a shorter time of stimulation compared to conventional rTMS protocols. Since its first description, TBS has been used in both basic and clinical research in the last years and more recently it has been expanded to other domains than the motor system. Its capacity to induce synaptic plasticity could lead to therapeutic implications for neuropsychiatric disorders. The neurobiological mechanisms of TBS are not fully understood at present; they may involve long-term potentiation (LTP)- and depression (LTD)-like processes, as well as inhibitory mechanisms modulated by GABAergic activity. This article highlights current hypotheses regarding the mechanisms of action of TBS and some central factors which may influence cortical responses to TBS. Furthermore, previous and ongoing research performed in the field of TBS on the motor cortex is summarized.

A method to determine the presence of averaged event-related fields using randomization tests.

Abstract: We present a simple and effective method to test whether an event consistently activates a set of brain electric sources across repeated measurements of event-related scalp field data. These repeated measurements can be single trials, single subject ERPs, or ERPs from different studies. The method considers all sensors simultaneously, but can be applied separately to each time frame or frequency band of the data. This allows limiting the analysis to time periods and frequency bands where there is positive evidence of a consistent relation between the event and some brain electric sources. The test may therefore avoid false conclusions about the data resulting from an inadequate selection of the analysis window and bandpass filter, and permit the exploration of alternate hypotheses when group/condition differences are observed in evoked field data. The test will be called topographic consistency test (TCT). The statistical inference is based on simple randomization techniques. Apart form the methodological introduction, the paper contains a series of simulations testing the statistical power of the method as function of number of sensors and observations, a sample analysis of EEG potentials related to self-initiated finger movements, and Matlab source code to facilitate the implementation. Furthermore a series of measures to control for multiple testing are introduced and applied to the sample data.

Changes in Brain Activity During the Observation of TV Commercials by Using EEG, GSR and HR Measurements

Abstract: In this study we were interested to analyse the brain activity occurring during the "naturalistic" observation of commercial ads intermingled in a random order within a documentary. In order to measure both the brain activity and the emotional engage of the 15 healthy subjects investigated, we used simultaneous EEG, Galvanic Skin Response (GSR), Heart Rate (HR) recordings during the whole experiment. We would like to link significant variation of EEG, GSR, HR and Heart Rate Variability (HRV) measurements with the memory and pleasantness of the stimuli presented, as resulted successively from the subject's verbal interview. In order to do that, different indexes were employed to summarize the cerebral and autonomic measurements performed. Such indexes were used in the statistical analysis, performed with the use of Analysis of Variance (ANOVA) and z-score transformation of the estimated cortical activity by solving the associated EEG inverse problem. The results are summarized as follows: (1) in the population analyzed, the cortical activity in the theta band elicited during the observation of the TV commercials that were remembered is higher and localized in the left frontal brain areas when compared to the activity elicited during the vision of the TV commercials that were forgotten (p < 0.048). Same increase in the theta activity occurred during the observation of commercials that were judgment pleasant when compared with the other (p < 0.042). Differences in cortical activity were also observed for the gamma activity, bilaterally in frontal and prefrontal areas. (2) the HR and HRV activity elicited during the observation of the TV commercials that were remembered or judged pleasant is higher than the same activity during the observation of commercials that will be forgotten (p < 0.001 and p < 0.048, respectively for HR and HRV) or were judged unpleasant (p < 0.042 and p < 0.04, respectively for HR and HRV). No statistical differences between the level of the GSR values were observed across the experimental conditions. In conclusion, the TV commercials proposed to the population analyzed have increased the HR values and the cerebral activity mainly in the theta band in the left hemisphere when they will be memorized and judged pleasant. Further research with an extended set of subjects will be necessary to further validate the observations reported in this paper. However, these conclusions seems reasonable and well inserted in the already existing literature on this topic related to the HERA model.

Neuroelectrical Hyperscanning Measures Simultaneous Brain Activity in Humans

Abstract: In this study we illustrate a methodology able to follow and study concurrent and simultaneous brain processes during cooperation between individuals, with non invasive EEG methodologies. We collected data from fourteen pairs of subjects while they were playing a card game with EEG. Data collection was made simultaneously on all the subjects during the card game. An extension of the Granger-causality approach allows us to estimate the functional connection between signals estimated from different Regions of Interest (ROIs) in different brains during the analyzed task. Finally, with the use of graph theory, we contrast the functional connectivity patterns of the two players belonging to the same team. Statistically significant functional connectivities were obtained from signals estimated in the ROIs modeling the anterior cingulate cortex (ACC) and the prefrontal areas described by the Brodmann areas 8 with the signals estimated in all the other modelled cortical areas. Results presented suggested the existence of Granger-sense causal relations between the EEG activity estimated in the prefrontal areas 8 and 9/46 of one player with the EEG activity estimated in the ACC of their companion. We illustrated the feasibility of functional connectivity methodology on the EEG hyperscannings performed on a group of subjects. These functional connectivity estimated from the couple of brains could suggest, in statistical and mathematical terms, the modelled cortical areas that are correlated in Granger-sense during the solution of a particular task. EEG hyperscannings could be used to investigate experimental paradigms where the knowledge of the simultaneous interactions between the subjects have a value.

Connecting mean field models of neural activity to EEG and fMRI data.

Abstract: Progress in functional neuroimaging of the brain increasingly relies on the integration of data from complementary imaging modalities in order to improve spatiotemporal resolution and interpretability. However, the usefulness of merely statistical combinations is limited, since neural signal sources differ between modalities and are related non-trivially. We demonstrate here that a mean field model of brain activity can simultaneously predict EEG and fMRI BOLD with proper signal generation and expression. Simulations are shown using a realistic head model based on structural MRI, which includes both dense short-range background connectivity and long-range specific connectivity between brain regions. The distribution of modeled neural masses is comparable to the spatial resolution of fMRI BOLD, and the temporal resolution of the modeled dynamics, importantly including activity conduction, matches the fastest known EEG phenomena. The creation of a cortical mean field model with anatomically sound geometry, extensive connectivity, and proper signal expression is an important first step towards the model-based integration of multimodal neuroimages.

Which Physiological Components are More Suitable for Visual ERP Based Brain–Computer Interface? A Preliminary MEG/EEG Study

Abstract: We investigated which evoked response component occurring in the first 800 ms after stimulus presentation was most suitable to be used in a classical P300-based brain-computer interface speller protocol. Data was acquired from 275 Magnetoencephalographic sensors in two subjects and from 61 Electroencephalographic sensors in four. To better characterize the evoked physiological responses and minimize the effect of response overlap, a 1000 ms Inter Stimulus Interval was preferred to the short (

Automatic Removal of Eye-Movement and Blink Artifacts from EEG Signals

Abstract: Frequent occurrence of electrooculography (EOG) artifacts leads to serious problems in interpreting and analyzing the electroencephalogram (EEG). In this paper, a robust method is presented to automatically eliminate eye-movement and eye-blink artifacts from EEG signals. Independent Component Analysis (ICA) is used to decompose EEG signals into independent components. Moreover, the features of topographies and power spectral densities of those components are extracted to identify eye-movement artifact components, and a support vector machine (SVM) classifier is adopted because it has higher performance than several other classifiers. The classification results show that feature-extraction methods are unsuitable for identifying eye-blink artifact components, and then a novel peak detection algorithm of independent component (PDAIC) is proposed to identify eye-blink artifact components. Finally, the artifact removal method proposed here is evaluated by the comparisons of EEG data before and after artifact removal. The results indicate that the method proposed could remove EOG artifacts effectively from EEG signals with little distortion of the underlying brain signals.

On optimal channel configurations for SMR-based brain-computer interfaces.

Abstract: One crucial question in the design of electroencephalogram (EEG)-based brain-computer interface (BCI) experiments is the selection of EEG channels. While a setup with few channels is more convenient and requires less preparation time, a dense placement of electrodes provides more detailed information and henceforth could lead to a better classification performance. Here, we investigate this question for a specific setting: a BCI that uses the popular CSP algorithm in order to classify voluntary modulations of sensorimotor rhythms (SMR). In a first approach 13 different fixed channel configurations are compared to the full one consisting of 119 channels. The configuration with 48 channels results to be the best one, while configurations with less channels, from 32 to 8, performed not significantly worse than the best configuration in cases where only few training trials are available. In a second approach an optimal channel configuration is obtained by an iterative procedure in the spirit of stepwise variable selection with nonparametric multiple comparisons. As a surprising result, in the second approach a setting with 22 channels centered over the motor areas was selected. Thanks to the acquisition of a large data set recorded from 80 novice participants using 119 EEG channels, the results of this study can be expected to have a high degree of generalizability.

Transmission of Brain Activity During Cognitive Task

Abstract: The transmission of brain activity during constant attention test was estimated by means of the short-time directed transfer function (SDTF). SDTF is an estimator based on a multivariate autoregressive model. It determines the propagation as a function of time and frequency. For nine healthy subjects the transmission of EEG activity was determined for target and non-target conditions corresponding to pressing of a switch in case of appearance of two identical images or withholding the reaction in case of different images. The involvement of prefrontal and frontal cortex manifested by the propagation from these structures was observed, especially in the early stages of the task. For the target condition there was a burst of propagation from C3 after pressing the switch, which can be interpreted as beta rebound upon completion of motor action. In case of non-target condition the propagation from F8 or Fz to C3 was observed, which can be connected with the active inhibition of motor cortex by right inferior frontal cortex or presupplementary motor area.

On the Origin of the N400 Effects: An ERP Waveform and Source Localization Analysis in Three Matching Tasks

Abstract: The question of the cognitive nature and the cerebral origins of the event-related potential (ERP) N400 component has frequently been debated. Here, the N400 effects were analyzed in three tasks. In the semantic task, subjects decided whether sequentially presented word pairs were semantically related or unrelated. In the phonologic (rhyme detection) task, they decided if words were phonologically related or not. In the image categorization task, they decided whether images were categorically related or not. Difference waves between ERPs to unrelated and related conditions (defined here as the N400 effect) demonstrated a greater amplitude and an earlier peak latency effect in the image than in semantic and phonologic tasks. In contrast, spatial correlation analysis revealed that the maps computed during the peak of the N400 effects were highly correlated. Source localization computed from these maps showed the involvement in all tasks of the middle/superior temporal gyrus. Our results suggest that these qualitatively similar N400 effects index the same cognitive content despite differences in the representational formats (words vs. images) and the types of mismatch (semantic vs. phonological) across tasks.

Integrating TMS with EEG: How and what for?

Abstract: This is one of several papers published together in Brain Topography on the "Special Topic: TMS and EEG".

Prospects for clinical applications of transcranial magnetic stimulation and real-time EEG in epilepsy.

Abstract: Recent advances in methods for transcranial magnetic stimulation (TMS) enable its coupling to real-time EEG (TMS-EEG). Although TMS-EEG is applied largely in neurophysiology research, there are prospects for its use in clinical TMS practice, particularly in epilepsy where EEG is already in wide use, and where TMS is emerging as a diagnostic and therapeutic tool. In diagnostic applications, TMS-EEG may provide a useful measure of cortical excitability at baseline or after antiepileptic treatment. For therapeutic purposes, TMS-EEG may be of use in selection of appropriate TMS strength outside of the motor cortex where the threshold for cortical activation is more apparent with the aid of EEG. In other realistic clinical applications, TMS-EEG may be of use in real-time monitoring for epileptiform activity in vulnerable populations where TMS may trigger seizures, or as a component of a responsive neurostimulation setup in which TMS timing is determined by underlying EEG activity. Future trials and evolution of TMS-EEG methods are likely to provide answers as to the actual clinical value of TMS-EEG.

Somatosensory System Deficits in Schizophrenia Revealed by MEG during a Median-Nerve Oddball Task

Abstract: Although impairments related to somatosensory perception are common in schizophrenia, they have rarely been examined in functional imaging studies. In the present study, magnetoencephalography (MEG) was used to identify neural networks that support attention to somatosensory stimuli in healthy adults and abnormalities in these networks in patient with schizophrenia. A median-nerve oddball task was used to probe attention to somatosensory stimuli, and an advanced, high-resolution MEG source-imaging method was applied to assess activity throughout the brain. In nineteen healthy subjects, attention-related activation was seen in a sensorimotor network involving primary somatosensory (S1), secondary somatosensory (S2), primary motor (M1), pre-motor (PMA), and paracentral lobule (PCL) areas. A frontal–parietal–temporal “attention network”, containing dorsal- and ventral–lateral prefrontal cortex (DLPFC and VLPFC), orbitofrontal cortex (OFC), anterior cingulate cortex (ACC), superior parietal lobule (SPL), inferior parietal lobule (IPL)/supramarginal gyrus (SMG), and temporal lobe areas, was also activated. Seventeen individuals with schizophrenia showed early attention-related hyperactivations in S1 and M1 but hypo-activation in S1, S2, M1, and PMA at later latency in the sensorimotor network. Within this attention network, hypoactivation was found in SPL, DLPFC, orbitofrontal cortex, and the dorsal aspect of ACC. Hyperactivation was seen in SMG/IPL, frontal pole, and the ventral aspect of ACC in patients. These findings link attention-related somatosensory deficits to dysfunction in both sensorimotor and frontal–parietal–temporal networks in schizophrenia.

Using EEG to explore how rTMS produces its effects on behavior

Abstract: A commonly held view is that, when delivered during the performance of a task, repetitive TMS (rTMS) influences behavior by producing transient “virtual lesions” in targeted tissue. However, findings of rTMS-related improvements in performance are difficult to reconcile with this assumption. With regard to the mechanism whereby rTMS influences concurrent task performance, a combined rTMS/EEG study conducted in our lab has revealed a complex set of relations between rTMS, EEG activity, and behavioral performance, with the effects of rTMS on power in the alpha band and on alpha:gamma phase synchrony each predicting its effect on behavior. These findings suggest that rTMS influences performance by biasing endogenous task-related oscillatory dynamics, rather than creating a “virtual lesion”. To further differentiate these two alternatives, in the present study we compared the effects of 10 Hz rTMS on neural activity with the results of an experiment in which rTMS was replaced with 10 Hz luminance flicker. We reasoned that 10 Hz flicker would produce widespread entrainment of neural activity to the flicker frequency, and comparison of these EEG results with those from the rTMS study would shed light on whether the latter also reflected entrainment to an exogenous stimulus. Results revealed pronounced evidence for “entrainment noise” produced by 10 Hz flicker—increased oscillatory power and inter-trial coherence (ITC) at the driving frequency, and increased alpha:gamma phase synchronization—that were nonetheless largely uncorrelated with behavior. This contrasts markedly with 10-Hz rTMS, for which the only evidence for stimulation-induced noise, elevated ITC at 30 Hz, differed qualitatively from the flicker results. Simultaneous recording of the EEG thus offers an important means of directly testing assumptions about how rTMS exerts its effects on behavior.

Regional differences in the sensitivity of MEG for interictal spikes in epilepsy.

Abstract: MEG interictal spikes as recorded in epilepsy patients are a reflection of intracranial interictal activity. This study investigates the relationship between the estimated sources of MEG spikes and the location, distribution and size of interictal spikes in the invasive ECoG of a group of 38 epilepsy patients that are monitored for pre-surgical evaluation. An amplitude/surface area measure is defined to quantify and rank ECoG spikes. It is found that all MEG spikes are associated with an ECoG spike that is among the three highest ranked in a patient. Among the different brain regions considered, the fronto-orbital, inter-hemispheric, tempero-lateral and central regions stand out. In an accompanying simulation study it is shown that for hypothesized extended sources of larger sizes, as suggested by the data, source location, orientation and curvature can partly explain the observed sensitivity of MEG for interictal spikes.

Cortical network analysis in patients affected by schizophrenia

Abstract: In the present study, we studied the structural changes of the brain functional network in a group of schizophrenic (SCHZ) patients during a 2-back working memory task. Cortical signals were obtained from scalp EEG signals through the high-resolution EEG technique, which relies on realistic head models and linear inverse solutions. Functional networks were estimated by computing the spectral coherence—i.e. a measure of synchronization in the frequency domain—between the time series of all the available cortical sources. To analyze those cortical networks we followed a theoretical graph approach by computing the network density as the total number of links and the node degree as the number of links of each cortical source. The major result suggest that in the Alpha2 frequency band (11–13 Hz) the cortical functional networks of the SCHZ patients present the largest differences when compared with those of a group of control (CTRL) subjects. In particular, the structure of the SCHZ network altered radically during the memory task, as the number of links that were different from the REST condition increased sensibly with respect to the CTRL network. In addition, a compensatory mechanism was found in the SCHZ patients during the correct performance of the memory task where the node degree showed a frontal asymmetry with higher activation of the left frontal lobe—i.e. higher number of connections—in the Alpha2 frequency band.

Information communication networks in severe traumatic brain injury

Abstract: In this study we explored the use of coherence and Granger causality (GC) to separate patients in minimally conscious state (MCS) from patients with severe neurocognitive disorders (SND) that show signs of awareness. We studied 16 patients, 7 MCS and 9 SND with age between 18 and 49 years. Three minutes of ongoing electroencephalographic (EEG) activity was obtained at rest from 19 standard scalp locations, while subjects were alert but kept their eyes closed. GC was formulated in terms of linear autoregressive models that predict the evolution of several EEG time series, each representing the activity of one channel. The entire network of causally connected brain areas can be summarized as a graph of incompletely connected nodes. The 19 channels were grouped into five gross anatomical regions, frontal, left and right temporal, central, and parieto-occipital, while data analysis was performed separately in each of the five classical EEG frequency bands, namely delta, theta, alpha, beta, and gamma. Our results showed that the SND group consistently formed a larger number of connections compared to the MCS group in all frequency bands. Additionally, the number of connections in the delta band (0.1-4 Hz) between the left temporal and parieto-occipital areas was significantly different (P < 0.1%) in the two groups. Furthermore, in the beta band (12-18 Hz), the input to the frontal areas from all other cortical areas was also significantly different (P < 0.1%) in the two groups. Finally, classification of the subjects into distinct groups using as features the number of connections within and between regions in all frequency bands resulted in 100% classification accuracy of all subjects. The results of this study suggest that analysis of brain connectivity networks based on GC can be a highly accurate approach for classifying subjects affected by severe traumatic brain injury.

Cortical connections between dorsal and ventral visual streams in humans: Evidence by TMS/EEG co-registration.

Abstract: Parietal cortex subserves various cognitive tasks, ranging from attention to visuo-motor skills. It is part of a parieto-frontal network involved in attention, and part of the visual dorsal stream, opposed to the visual ventral stream, although increasing evidence suggests interchange of information between them. In this study, co-registration of Transcranial Magnetic Stimulation (TMS) and Electroencephalographic activity (EEG) has been used to investigate the spreading of cortical connections from the parietal cortex in healthy volunteers. TMS on the left parietal cortex activated a network of prefrontal regions in the contra-lateral hemisphere in a time range of 102-167 ms after the stimulus. Moreover, activation in the ipsi-lateral middle temporal and fusiform gyri was observed at 171-177 ms after delivery of TMS. Findings suggest the existence of late driven connections between parietal and prefrontal regions that could partially represent the neural pathway related to attention, even if, in this experiment, no attentional processing was requested. Late connections between dorsal and ventral streams were also evident, confirming previous evidence about interchange of information between them. Conclusively, the present investigation confirms that a great amount of information spreads from parietal cortex to different regions in the brain, supporting the idea that connections are more complex and articulated than those proposed. Present findings also suggest that the simultaneous recording of EEG during the application of TMS is a promising tool for the study of connections in the brain.

The neural bases of word encoding and retrieval: A fMRI-guided transcranial magnetic stimulation study

Abstract: There is evidence that the human prefrontal cortex is asymmetrically involved in long-term episodic memory processing. Moreover, abstract and concrete words processing has been reported to differentially involve prefrontal and parietal areas. We implemented a two-stages functional magnetic resonance imaging (fMRI)-repetitive transcranial magnetic stimulation (rTMS) paradigm to investigate the role of the dorsolateral prefrontal cortices (DLPFCs) and parietal cortices (PARCs) in encoding and retrieval of abstract and concrete words. Using this paradigm we could select areas to be stimulated on the basis of single-subject (SS) anatomical and functional data, investigating the usefulness of this integration approach. With respect to fMRI, abstract and concrete words differed only for a greater left fusiform gyrus activation for concrete words. In turn, significant rTMS effects were found, but only for the retrieval of abstract words. Consistent with previous findings, repetitive stimulation of the right DLPFC had a specific impact on episodic retrieval. Memory retrieval performance was also disrupted when rTMS was applied to the left PARC. Finally, we found a significant positive correlation between the effect sizes of SS right PARC activations for abstract word retrieval and the consequent rTMS interference effects. Taken together these data provide for the first time evidence that also the PARC has a necessary role in episodic retrieval of abstract words. Importantly, from a methodological perspective, our data demonstrate that fMRI-guided rTMS with a SS approach provides a powerful tool to investigate the neural underpinnings of cognitive functions.

On the “Dependence” of “Independent” Group EEG Sources; an EEG Study on Two Large Databases

Abstract: The aim of this work is to study the coherence profile (dependence) of robust eyes-closed resting EEG sources isolated by group blind source separation (gBSS). We employ a test-retest strategy using two large sample normative databases (N = 57 and 84). Using a BSS method in the complex Fourier domain, we show that we can rigourously study the out-of-phase dependence of the extracted components, albeit they are extracted so as to be in-phase independent (by BSS definition). Our focus on lagged communication between components effectively yields dependence measures unbiased by volume conduction effects, which is a major concern about the validity of any dependence measures issued by EEG measurements. We are able to show the organization of the extracted components in two networks. Within each network components oscillate coherently with multiple-frequency dynamics, whereas between networks they exchange information at non-random multiple time-lag rates.

Mental imagery for full and upper human bodies: common right hemisphere activations and distinct extrastriate activations.

Abstract: The processing of human bodies is important in social life and for the recognition of another person’s actions, moods, and intentions. Recent neuroimaging studies on mental imagery of human body parts suggest that the left hemisphere is dominant in body processing. However, studies on mental imagery of full human bodies reported stronger right hemisphere or bilateral activations. Here, we measured functional magnetic resonance imaging during mental imagery of bilateral partial (upper) and full bodies. Results show that, independently of whether a full or upper body is processed, the right hemisphere (temporo-parietal cortex, anterior parietal cortex, premotor cortex, bilateral superior parietal cortex) is mainly involved in mental imagery of full or partial human bodies. However, distinct activations were found in extrastriate cortex for partial bodies (right fusiform face area) and full bodies (left extrastriate body area). We propose that a common brain network, mainly on the right side, is involved in the mental imagery of human bodies, while two distinct brain areas in extrastriate cortex code for mental imagery of full and upper bodies.

Comparing ICA-based and single-trial topographic ERP analyses.

Abstract: Single-trial analysis of human electroencephalography (EEG) has been recently proposed for better understanding the contribution of individual subjects to a group-analyis effect as well as for investigating single-subject mechanisms. Independent Component Analysis (ICA) has been repeatedly applied to concatenated single-trial responses and at a single-subject level in order to extract those components that resemble activities of interest. More recently we have proposed a single-trial method based on topographic maps that determines which voltage configurations are reliably observed at the event-related potential (ERP) level taking advantage of repetitions across trials. Here, we investigated the correspondence between the maps obtained by ICA versus the topographies that we obtained by the single-trial clustering algorithm that best explained the variance of the ERP. To do this, we used exemplar data provided from the EEGLAB website that are based on a dataset from a visual target detection task. We show there to be robust correpondence both at the level of the activation time courses and at the level of voltage configurations of a subset of relevant maps. We additionally show the estimated inverse solution (based on low-resolution electromagnetic tomography) of two corresponding maps occurring at approximately 300 ms post-stimulus onset, as estimated by the two aforementioned approaches. The spatial distribution of the estimated sources significantly correlated and had in common a right parietal activation within Brodmann’s Area (BA) 40. Despite their differences in terms of theoretical bases, the consistency between the results of these two approaches shows that their underlying assumptions are indeed compatible.

Multimodal integration of fMRI and EEG data for high spatial and temporal resolution analysis of brain networks

Abstract: Two major non-invasive brain mapping techniques, electroencephalography (EEG) and functional magnetic resonance imaging (fMRI), have complementary advantages with regard to their spatial and temporal resolution. We propose an approach based on the integration of EEG and fMRI, enabling the EEG temporal dynamics of information processing to be characterized within spatially well-defined fMRI large-scale networks. First, the fMRI data are decomposed into networks by means of spatial independent component analysis (sICA), and those associated with intrinsic activity and/or responding to task performance are selected using information from the related time-courses. Next, the EEG data over all sensors are averaged with respect to event timing, thus calculating event-related potentials (ERPs). The ERPs are subjected to temporal ICA (tICA), and the resulting components are localized with the weighted minimum norm (WMNLS) algorithm using the task-related fMRI networks as priors. Finally, the temporal contribution of each ERP component in the areas belonging to the fMRI large-scale networks is estimated. The proposed approach has been evaluated on visual target detection data. Our results confirm that two different components, commonly observed in EEG when presenting novel and salient stimuli, respectively, are related to the neuronal activation in large-scale networks, operating at different latencies and associated with different functional processes.

Cerebral Hemodynamic Responses Induced by Specific Acupuncture Sensations During Needling at Trigger Points: A Near-Infrared Spectroscopic Study

Abstract: Acupuncture stimulation at specific points, or trigger points (TPs), elicits sensations called “de-qi”. De-qi sensations relate to the clinical efficacy of the treatment. However, it is neither clear whether de-qi sensations are associated with TPs, nor clear whether acupuncture effects on brain activity are associated with TPs or de-qi. We recorded cerebral hemodynamic responses during acupuncture stimulation at TPs and non-TPs by functional near-infrared spectroscopy. The acupuncture needle was inserted into both TPs and non-TPs within the right extensor muscle in the forearm. Typical acupuncture needle manipulation was conducted eight times for 15 s. The subjects pressed a button if they felt a de-qi sensation. We investigated how hemodynamic responses related to de-qi sensations induced at TPs and non-TPs. We observed that acupuncture stimulations producing de-qi sensations significantly decreased the Oxy-Hb concentration in the supplementary motor area (SMA), pre-supplementary motor area, and anterior dorsomedial prefrontal cortex regardless of the point stimulated. The hemodynamic responses were statistically analyzed using a general linear model and a boxcar function approximating the hemodynamic response. We observed that hemodynamic responses best fit the boxcar function when an onset delay was introduced into the analyses, and that the latency of de-qi sensations correlated with the onset delay of the best-fit function applied to the SMA. Our findings suggest that de-qi sensations favorably predict acupuncture effects on cerebral hemodynamics regardless of the type of site stimulated. Also, the effect of acupuncture stimulation in producing de-qi sensation was partly mediated by the central nervous system including the SMA.